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<p>During the last decade, urban growth and the simultaneous increase in vehicle numbers have created numerous challenges. Despite significant efforts to alleviate transportation issues in Tehran, traffic congestion has worsened, leading to increased air pollution, fuel consumption, and health problems, along with wasted time. In Tehran, there are 13 million daily trips, with 41% made by private cars, often underutilizing their capacity. This research aims to reduce traffic from single-occupant vehicles by developing a system that connects drivers and passengers with similar routes. This approach not only decreases the number of single-occupant vehicles but also enhances traffic flow, reduces fuel consumption, and lowers air pollution. Additionally, drivers can earn fees for sharing their empty seats, making their commutes more economical. To optimize routing for ridesharing, we employed meta-heuristic methods due to the increased complexity with more passengers and vehicles. The Tabu search (TS) algorithm was utilized in this study. Subsequently, the 2nd district of Tehran was selected as the test area, and two scenarios for implementing the designed algorithm were analyzed with varying parameters regarding the number of passengers and drivers. This resulted in solution times of 25–40&#xa0;s, indicating that the TS method, combined with GIS network analysis, demonstrates high stability and precision in addressing the vehicle routing problem (VPR).</p>

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Ridesharing optimization using GIS & TS algorithm based on spatial methods

  • 期刊论文

  • 发表日期：

    2025年6月1日

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  • Seyedeh Saharnaz Gol Chehreh Rahimi,
  • Saeed Behzadi,
  • Hossein Aghamohammadi Zanjirabad,
  • Alireza Sharifi,
  • Alireza Vafaeinejad

摘要

During the last decade, urban growth and the simultaneous increase in vehicle numbers have created numerous challenges. Despite significant efforts to alleviate transportation issues in Tehran, traffic congestion has worsened, leading to increased air pollution, fuel consumption, and health problems, along with wasted time. In Tehran, there are 13 million daily trips, with 41% made by private cars, often underutilizing their capacity. This research aims to reduce traffic from single-occupant vehicles by developing a system that connects drivers and passengers with similar routes. This approach not only decreases the number of single-occupant vehicles but also enhances traffic flow, reduces fuel consumption, and lowers air pollution. Additionally, drivers can earn fees for sharing their empty seats, making their commutes more economical. To optimize routing for ridesharing, we employed meta-heuristic methods due to the increased complexity with more passengers and vehicles. The Tabu search (TS) algorithm was utilized in this study. Subsequently, the 2nd district of Tehran was selected as the test area, and two scenarios for implementing the designed algorithm were analyzed with varying parameters regarding the number of passengers and drivers. This resulted in solution times of 25–40 s, indicating that the TS method, combined with GIS network analysis, demonstrates high stability and precision in addressing the vehicle routing problem (VPR).